Wrap grdview

doc/api/index.rst

@@ -29,6 +29,7 @@ Plotting data and laying out the map:
     Figure.contour
     Figure.grdcontour
     Figure.grdimage
+    Figure.grdview
     Figure.legend
     Figure.logo
     Figure.image

pygmt/base_plotting.py

@@ -2,6 +2,7 @@
 Base class with plot generating commands.
 Does not define any special non-GMT methods (savefig, show, etc).
 """
+import contextlib
 import csv
 import os
 import numpy as np
@@ -318,6 +319,114 @@ def grdimage(self, grid, **kwargs):
                 arg_str = " ".join([fname, build_arg_string(kwargs)])
                 lib.call_module("grdimage", arg_str)
 
+    @fmt_docstring
+    @use_alias(
+        R="region",
+        J="projection",
+        Jz="zscale",
+        JZ="zsize",
+        B="frame",
+        C="cmap",
+        G="drapegrid",
+        N="plane",
+        Q="surftype",
+        Wc="contourpen",
+        Wm="meshpen",
+        Wf="facadepen",
+        p="perspective",
+    )
+    @kwargs_to_strings(R="sequence", p="sequence")
+    def grdview(self, grid, **kwargs):
+        """
+        Create 3-D perspective image or surface mesh from a grid.
+
+        Reads a 2-D grid file and produces a 3-D perspective plot by drawing a
+        mesh, painting a colored/gray-shaded surface made up of polygons, or by
+        scanline conversion of these polygons to a raster image. Options
+        include draping a data set on top of a surface, plotting of contours on
+        top of the surface, and apply artificial illumination based on
+        intensities provided in a separate grid file.
+
+        Full option list at :gmt-docs:`grdview.html`
+
+        Parameters
+        ----------
+        grid : str or xarray.DataArray
+            The file name of the input relief grid or the grid loaded as a
+            DataArray.
+
+        zscale/zsize : float or str
+            Set z-axis scaling or z-axis size.
+
+        cmap : str
+            The name of the color palette table to use.
+
+        drapegrid : str or xarray.DataArray
+            The file name or a DataArray of the image grid to be draped on top
+            of the relief provided by grid. [Default determines colors from
+            grid]. Note that -Jz and -N always refers to the grid. The
+            drapegrid only provides the information pertaining to colors, which
+            (if drapegrid is a grid) will be looked-up via the CPT (see -C).
+
+        plane : float or str
+            ``level[+gfill]``.
+            Draws a plane at this z-level. If the optional color is provided
+            via the +g modifier, and the projection is not oblique, the frontal
+            facade between the plane and the data perimeter is colored.
+
+        surftype : str
+            Specifies cover type of the grid.
+            Select one of following settings:
+            1. 'm' for mesh plot [Default].
+            2. 'mx' or 'my' for waterfall plots (row or column profiles).
+            3. 's' for surface plot.
+            4. 'i' for image plot.
+            5. 'c'. Same as 'i' but will make nodes with z = NaN transparent.
+            For any of these choices, you may force a monochrome image by
+            appending the modifier +m.
+
+        contourpen : str
+            Draw contour lines on top of surface or mesh (not image). Append
+            pen attributes used for the contours.
+        meshpen : str
+            Sets the pen attributes used for the mesh. You must also select -Qm
+            or -Qsm for meshlines to be drawn.
+        facadepen :str
+            Sets the pen attributes used for the facade. You must also select
+            -N for the facade outline to be drawn.
+
+        perspective : list or str
+            ``'[x|y|z]azim[/elev[/zlevel]][+wlon0/lat0[/z0]][+vx0/y0]'``.
+            Select perspective view.
+
+        {aliases}
+        """
+        kwargs = self._preprocess(**kwargs)
+        kind = data_kind(grid, None, None)
+        with Session() as lib:
+            if kind == "file":
+                file_context = dummy_context(grid)
+            elif kind == "grid":
+                file_context = lib.virtualfile_from_grid(grid)
+            else:
+                raise GMTInvalidInput(f"Unrecognized data type for grid: {type(grid)}")
+
+            with contextlib.ExitStack() as stack:
+                fname = stack.enter_context(file_context)
+                if "G" in kwargs:
+                    drapegrid = kwargs["G"]
+                    if data_kind(drapegrid) in ("file", "grid"):
+                        if data_kind(drapegrid) == "grid":
+                            drape_context = lib.virtualfile_from_grid(drapegrid)
+                            drapefile = stack.enter_context(drape_context)
+                            kwargs["G"] = drapefile
+                    else:
+                        raise GMTInvalidInput(
+                            f"Unrecognized data type for drapegrid: {type(drapegrid)}"
+                        )
+                arg_str = " ".join([fname, build_arg_string(kwargs)])
+                lib.call_module("grdview", arg_str)
+
     @fmt_docstring
     @use_alias(
         R="region",

pygmt/tests/test_grdview.py

@@ -0,0 +1,218 @@
+# pylint: disable=redefined-outer-name
+"""
+Tests grdview
+"""
+import pytest
+
+from .. import Figure, which
+from ..datasets import load_earth_relief
+from ..exceptions import GMTInvalidInput
+from ..helpers import data_kind
+
+
+@pytest.fixture(scope="module")
+def grid():
+    "Load the grid data from the sample earth_relief file"
+    return load_earth_relief().sel(lat=slice(-49, -42), lon=slice(-118, -107))
+
+
+@pytest.mark.mpl_image_compare
+def test_grdview_grid_dataarray(grid):
+    """
+    Run grdview by passing in a grid as an xarray.DataArray.
+    """
+    fig = Figure()
+    fig.grdview(grid=grid)
+    return fig
+
+
+@pytest.mark.mpl_image_compare
+def test_grdview_grid_file_with_region_subset():
+    """
+    Run grdview by passing in a grid filename, and cropping it to a region.
+    """
+    gridfile = which("@earth_relief_60m", download="c")
+
+    fig = Figure()
+    fig.grdview(grid=gridfile, region=[-116, -109, -47, -44])
+    return fig
+
+
+def test_grdview_wrong_kind_of_grid(grid):
+    """
+    Run grdview using grid input that is not an xarray.DataArray or file.
+    """
+    dataset = grid.to_dataset()  # convert xarray.DataArray to xarray.Dataset
+    assert data_kind(dataset) == "matrix"
+
+    fig = Figure()
+    with pytest.raises(GMTInvalidInput):
+        fig.grdview(grid=dataset)
+
+
+@pytest.mark.mpl_image_compare
+def test_grdview_with_perspective(grid):
+    """
+    Run grdview by passing in a grid and setting a perspective viewpoint with
+    an azimuth from the SouthEast and an elevation angle 15 degrees from the
+    z-plane.
+    """
+    fig = Figure()
+    fig.grdview(grid=grid, perspective=[135, 15])
+    return fig
+
+
+@pytest.mark.mpl_image_compare
+def test_grdview_with_perspective_and_zscale(grid):
+    """
+    Run grdview by passing in a grid and setting a perspective viewpoint with
+    an azimuth from the SouthWest and an elevation angle 30 degrees from the
+    z-plane, plus a z-axis scaling factor of 0.005.
+    """
+    fig = Figure()
+    fig.grdview(grid=grid, perspective=[225, 30], zscale=0.005)
+    return fig
+
+
+@pytest.mark.mpl_image_compare
+def test_grdview_with_perspective_and_zsize(grid):
+    """
+    Run grdview by passing in a grid and setting a perspective viewpoint with
+    an azimuth from the SouthWest and an elevation angle 30 degrees from the
+    z-plane, plus a z-axis size of 10cm.
+    """
+    fig = Figure()
+    fig.grdview(grid=grid, perspective=[225, 30], zsize="10c")
+    return fig
+
+
+@pytest.mark.mpl_image_compare
+def test_grdview_with_cmap_for_image_plot(grid):
+    """
+    Run grdview by passing in a grid and setting a colormap for producing an
+    image plot.
+    """
+    fig = Figure()
+    fig.grdview(grid=grid, cmap="oleron", surftype="i")
+    return fig
+
+
+@pytest.mark.mpl_image_compare
+def test_grdview_with_cmap_for_surface_monochrome_plot(grid):
+    """
+    Run grdview by passing in a grid and setting a colormap for producing a
+    surface monochrome plot.
+    """
+    fig = Figure()
+    fig.grdview(grid=grid, cmap="oleron", surftype="s+m")
+    return fig
+
+
+@pytest.mark.mpl_image_compare
+def test_grdview_with_cmap_for_perspective_surface_plot(grid):
+    """
+    Run grdview by passing in a grid and setting a colormap for producing a
+    surface plot with a 3D perspective viewpoint.
+    """
+    fig = Figure()
+    fig.grdview(
+        grid=grid, cmap="oleron", surftype="s", perspective=[225, 30], zscale=0.005,
+    )
+    return fig
+
+
+@pytest.mark.mpl_image_compare
+def test_grdview_on_a_plane(grid):
+    """
+    Run grdview by passing in a grid and plotting it on a z-plane, while
+    setting a 3D perspective viewpoint.
+    """
+    fig = Figure()
+    fig.grdview(grid=grid, plane=-4000, perspective=[225, 30], zscale=0.005)
+    return fig
+
+
+@pytest.mark.mpl_image_compare
+def test_grdview_on_a_plane_with_colored_frontal_facade(grid):
+    """
+    Run grdview by passing in a grid and plotting it on a z-plane whose frontal
+    facade is colored gray, while setting a 3D perspective viewpoint.
+    """
+    fig = Figure()
+    fig.grdview(grid=grid, plane="-4000+ggray", perspective=[225, 30], zscale=0.005)
+    return fig
+
+
+@pytest.mark.mpl_image_compare
+def test_grdview_with_perspective_and_zaxis_frame(grid):
+    """
+    Run grdview by passing in a grid and plotting an annotated vertical
+    z-axis frame.
+    """
+    fig = Figure()
+    fig.grdview(grid=grid, perspective=[225, 30], zscale=0.005, frame="zaf")
+    return fig
+
+
+@pytest.mark.mpl_image_compare
+def test_grdview_surface_plot_styled_with_contourpen(grid):
+    """
+    Run grdview by passing in a grid with styled contour lines plotted on top
+    of a surface plot.
+    """
+    fig = Figure()
+    fig.grdview(grid=grid, cmap="relief", surftype="s", contourpen="0.5p,black,dash")
+    return fig
+
+
+@pytest.mark.mpl_image_compare
+def test_grdview_surface_mesh_plot_styled_with_meshpen(grid):
+    """
+    Run grdview by passing in a grid with styled mesh lines plotted on top of a
+    surface mesh plot.
+    """
+    fig = Figure()
+    fig.grdview(grid=grid, cmap="relief", surftype="sm", meshpen="0.5p,black,dash")
+    return fig
+
+
+@pytest.mark.mpl_image_compare
+def test_grdview_on_a_plane_styled_with_facadepen(grid):
+    """
+    Run grdview by passing in a grid and plotting it on a z-plane with styled
+    lines for the frontal facade.
+    """
+    fig = Figure()
+    fig.grdview(
+        grid=grid,
+        plane=-4000,
+        perspective=[225, 30],
+        zscale=0.005,
+        facadepen="0.5p,blue,dash",
+    )
+    return fig
+
+
+@pytest.mark.mpl_image_compare
+def test_grdview_drapegrid_dataarray(grid):
+    """
+    Run grdview by passing in both a grid and drapegrid as an xarray.DataArray,
+    setting a colormap for producing an image plot.
+    """
+    drapegrid = 1.1 * grid
+
+    fig = Figure()
+    fig.grdview(grid=grid, drapegrid=drapegrid, cmap="oleron", surftype="c")
+    return fig
+
+
+def test_grdview_wrong_kind_of_drapegrid(grid):
+    """
+    Run grdview using drapegrid input that is not an xarray.DataArray or file.
+    """
+    dataset = grid.to_dataset()  # convert xarray.DataArray to xarray.Dataset
+    assert data_kind(dataset) == "matrix"
+
+    fig = Figure()
+    with pytest.raises(GMTInvalidInput):
+        fig.grdview(grid=grid, drapegrid=dataset)